scholarly journals Laterally filtered 1D inversions of small-loop, frequency-domain EMI data from a chemical waste site

Geophysics ◽  
2008 ◽  
Vol 73 (4) ◽  
pp. F143-F149 ◽  
Author(s):  
Patricia Martinelli ◽  
María Celeste Duplaá
Keyword(s):  
Frequency Domain ◽  
Original Data ◽  
Inversion Method ◽  
Chemical Waste ◽  
Spatial Filters ◽  
Inverse Models ◽  
Anomalous Zone ◽  
Small Loop ◽  
Underground Contamination ◽  
2D Images

We made a study in the backyard of an agrochemical plant using a small-loop, frequency-domain electromagnetic induction (EMI) system. Such systems are very sensitive to conductive structures buried at shallow depths. Frequently, they are only used to locate and delimit these structures by direct observation of data. However, much more information can be obtained by applying numerical modeling techniques to the data. First we mapped an anomalous zone that indicates the possible presence of buried waste or some other underground contamination by visualizing data. Then we applied a 1D inversion method to the data from this zone. By joining 1D inversion results, this method builds 2D images of the subsoil structure below survey lines. Because the code applies smoothness constraints to the 1D inversions, the subsoil properties in these 2D images change gradually with depth. The code does not impose any correlation between the data or 1D models corresponding to neighboring points, so sharp lateral changes can appear. Several of them do not represent real features of the subsoil. We designed and applied two spatial filters to smooth the spurious lateral variations in our models. One correlates the data acquired at adjacent points prior to inversions. The other applies an analogous correlation to the inverse models obtained from the original data. Both filters greatly improve the quality of the 2D images. Compiling these results, we obtained a 3D model of the subsoil that characterizes the anomalous structure. Excavations made later at the site confirmed the results.

Frequency‐domain acoustic‐wave modeling and inversion of crosshole data: Part II—Inversion method, synthetic experiments and real‐data results

Geophysics ◽  
1995 ◽  
Vol 60 (3) ◽  
pp. 796-809 ◽  
Author(s):  
Zhong‐Min Song ◽  
Paul R. Williamson ◽  
R. Gerhard Pratt
Keyword(s):  
Frequency Domain ◽  
Real Data ◽  
Forward Modeling ◽  
Two Dimensions ◽  
Inversion Method ◽  
Inversion Algorithm ◽  
Data Set ◽  
Wave Inversion ◽  
Full Wave ◽  
And Inversion

In full‐wave inversion of seismic data in complex media it is desirable to use finite differences or finite elements for the forward modeling, but such methods are still prohibitively expensive when implemented in 3-D. Full‐wave 2-D inversion schemes are of limited utility even in 2-D media because they do not model 3-D dynamics correctly. Many seismic experiments effectively assume that the geology varies in two dimensions only but generate 3-D (point source) wavefields; that is, they are “two‐and‐one‐half‐dimensional” (2.5-D), and this configuration can be exploited to model 3-D propagation efficiently in such media. We propose a frequency domain full‐wave inversion algorithm which uses a 2.5-D finite difference forward modeling method. The calculated seismogram can be compared directly with real data, which allows the inversion to be iterated. We use a descents‐related method to minimize a least‐squares measure of the wavefield mismatch at the receivers. The acute nonlinearity caused by phase‐wrapping, which corresponds to time‐domain cycle‐skipping, is avoided by the strategy of either starting the inversion using a low frequency component of the data or constructing a starting model using traveltime tomography. The inversion proceeds by stages at successively higher frequencies across the observed bandwidth. The frequency domain is particularly efficient for crosshole configurations and also allows easy incorporation of attenuation, via complex velocities, in both forward modeling and inversion. This also requires the introduction of complex source amplitudes into the inversion as additional unknowns. Synthetic studies show that the iterative scheme enables us to achieve the theoretical maximum resolution for the velocity reconstruction and that strongly attenuative zones can be recovered with reasonable accuracy. Preliminary results from the application of the method to a real data set are also encouraging.

Frequency-domain synthesis of modified matched spatial filters

1985 ◽  
Vol 10 (11) ◽  
pp. 517 ◽  
Author(s):  
William A. Rozzi ◽  
David Casasent
Keyword(s):  
Frequency Domain ◽  
Spatial Filters

Comparison of source-independent methods of elastic waveform inversion

Geophysics ◽  
2006 ◽  
Vol 71 (6) ◽  
pp. R91-R100 ◽  
Author(s):  
Kun Xu ◽  
Stewart A. Greenhalgh ◽  
MiaoYue Wang
Keyword(s):  
Elastic Wave ◽  
Frequency Domain ◽  
Numerical Experiments ◽  
Random Noise ◽  
Waveform Inversion ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Practical Procedure ◽  
Wave Inversion ◽  
Full Waveform

In this paper, we investigate several source-independent methods of nonlinear full-waveform inversion of multicomponent elastic-wave data. This includes iterative estimation of source signature (IES), standard trace normalization (STN), and average trace normalization (ATN) inversion methods. All are based on the finite-element method in the frequency domain. One synthetic elastic crosshole model is used to compare the recovered images with all these methods as well as the known source signature (KSS) inversion method. The numerical experiments show that the IES method is superior to both STN and ATN methods in two-component, elastic-wave inversion in the frequency domain when the source signature is unknown. The STN and ATN methods have limitations associated with near-zero amplitudes (or polarity reversals) in traces from one of the components, which destroy the energy balance in the normalized traces and cause a loss of frequency information. But the ATN method is somewhat superior to the STN method in suppressing random noise and improving stability, as the developed formulas and the numerical experiments show. We suggest the IES method as a practical procedure for multicomponent seismic inversion.

Application of frequency-domain waveform inversion method in Marmousi shots data

2012 ◽  
Vol 17 (4) ◽  
pp. 326-330 ◽  
Author(s):  
Meng Wang ◽  
Dong Zhang ◽  
Di Yao ◽  
Qianqing Qin ◽  
Lin Xu
Keyword(s):  
Frequency Domain ◽  
Waveform Inversion ◽  
Inversion Method

scholarly journals Comparison of four inverse modelling systems applied to the estimation of HFC-125, HFC-134a, and SF<sub>6</sub> emissions over Europe

2017 ◽  
Vol 17 (17) ◽  
pp. 10651-10674 ◽  
Author(s):  
Dominik Brunner ◽  
Tim Arnold ◽  
Stephan Henne ◽  
Alistair Manning ◽  
Rona L. Thompson ◽  
...  
Keyword(s):  
Time Series ◽  
Global Warming ◽  
Greenhouse Gases ◽  
A Priori ◽  
Model Systems ◽  
Measurement Time ◽  
Inversion Method ◽  
Inverse Models ◽  
Hfc 134A ◽  
The Uk

Abstract. Hydrofluorocarbons (HFCs) are used in a range of industrial applications and have largely replaced previously used gases (CFCs and HCFCs). HFCs are not ozone-depleting but have large global warming potentials and are, therefore, reported to the United Nations Framework Convention on Climate Change (UNFCCC). Here, we use four independent inverse models to estimate European emissions of the two HFCs contributing the most to global warming (HFC-134a and HFC-125) and of SF6 for the year 2011. Using an ensemble of inverse models offers the possibility to better understand systematic uncertainties in inversions. All systems relied on the same measurement time series from Jungfraujoch (Switzerland), Mace Head (Ireland), and Monte Cimone (Italy) and the same a priori estimates of the emissions, but differed in terms of the Lagrangian transport model (FLEXPART, NAME), inversion method (Bayesian, extended Kalman filter), treatment of baseline mole fractions, spatial gridding, and a priori uncertainties. The model systems were compared with respect to the ability to reproduce the measurement time series, the spatial distribution of the posterior emissions, uncertainty reductions, and total emissions estimated for selected countries. All systems were able to reproduce the measurement time series very well, with prior correlations between 0.5 and 0.9 and posterior correlations being higher by 0.05 to 0.1. For HFC-125, all models estimated higher emissions from Spain + Portugal than reported to UNFCCC (median higher by 390 %) though with a large scatter between individual estimates. Estimates for Germany (+140 %) and Ireland (+850 %) were also considerably higher than UNFCCC, whereas the estimates for France and the UK were consistent with the national reports. In contrast to HFC-125, HFC-134a emissions from Spain + Portugal were broadly consistent with UNFCCC, and emissions from Germany were only 30 % higher. The data suggest that the UK over-reports its HFC-134a emissions to UNFCCC, as the model median emission was significantly lower, by 50 %. An overestimation of both HFC-125 and HFC-134a emissions by about a factor of 2 was also found for a group of eastern European countries (Czech Republic + Poland + Slovakia), though with less confidence since the measurement network has a low sensitivity to these countries. Consistent with UNFCCC, the models identified Germany as the highest national emitter of SF6 in Europe, and the model median emission was only 1 % lower than the UNFCCC numbers. In contrast, the model median emissions were 2–3 times higher than UNFCCC numbers for Italy, France, and Spain + Portugal. The country-aggregated emissions from the different models often did not overlap within the range of the analytical uncertainties formally given by the inversion systems, suggesting that parametric and structural uncertainties are often dominant in the overall a posteriori uncertainty. The current European network of three routine monitoring sites for synthetic greenhouse gases has the potential to identify significant shortcomings in nationally reported emissions, but a denser network would be needed for more reliable monitoring of country-wide emissions of these important greenhouse gases across Europe.

Elastic frequency-domain finite-difference contrast source inversion method

2016 ◽  
Vol 32 (3) ◽  
pp. 035009 ◽  
Author(s):  
Qinglong He ◽  
Yong Chen ◽  
Bo Han ◽  
Yang Li
Keyword(s):  
Finite Difference ◽  
Frequency Domain ◽  
Inversion Method ◽  
Source Inversion ◽  
Contrast Source Inversion

scholarly journals Resistivity and offset error estimations for the small-loop electromagnetic method

Geophysics ◽  
2008 ◽  
Vol 73 (3) ◽  
pp. F91-F95 ◽  
Author(s):  
Yutaka Sasaki ◽  
Jeong-Sul Son ◽  
Changryol Kim ◽  
Jung-Ho Kim
Keyword(s):  
Real Data ◽  
Staggered Grid ◽  
Inversion Method ◽  
Quality Of Data ◽  
Small Loop ◽  
Em Method ◽  
Error Estimations ◽  
2.5D Finite Element ◽  
Do So

Handheld frequency-domain electromagnetic (EM) instruments are being used increasingly for shallow environmental and geotechnical surveys because of their portability and speed of use in field operations. However, in many cases, the quality of data is so poor that quantitative interpretation is not justified. This is because the small-loop EM method is required to detect very weak signals (the secondary magnetic fields) in the presence of the dominant primary field, so the data are inherently susceptible to calibration errors. Although these errors can be measured by raising the instrument high above the ground so that the effect of the conducting ground is negligible, it is impracticable to do so for every survey. We have developed an algorithm that simultaneously inverts small-loop EM data for a multidimensional resistivity distribution and offset errors. For this inversion method to work successfully the data must be collected at two heights. The forward modeling used in the inversion is based on a staggered-grid 3D finite-difference method; its solution has been checked against a 2.5D finite-element solution. Synthetic and real data examples demonstrate that the inversion recovers reliable resistivity models from multifrequency data that are contaminated severely by offset errors.

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